{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6d0f4d87",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 语义分割和数据集\n",
    "\n",
    "最重要的语义分割数据集之一是[Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "78b0e57d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:34:46.209719Z",
     "iopub.status.busy": "2022-07-31T02:34:46.209168Z",
     "iopub.status.idle": "2022-07-31T02:35:43.622832Z",
     "shell.execute_reply": "2022-07-31T02:35:43.622127Z"
    },
    "origin_pos": 4,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading ../data/VOCtrainval_11-May-2012.tar from http://d2l-data.s3-accelerate.amazonaws.com/VOCtrainval_11-May-2012.tar...\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import torch\n",
    "import torchvision\n",
    "from d2l import torch as d2l\n",
    "\n",
    "d2l.DATA_HUB['voc2012'] = (d2l.DATA_URL + 'VOCtrainval_11-May-2012.tar',\n",
    "                           '4e443f8a2eca6b1dac8a6c57641b67dd40621a49')\n",
    "\n",
    "voc_dir = d2l.download_extract('voc2012', 'VOCdevkit/VOC2012')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04b97fc5",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "将所有输入的图像和标签读入内存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "21a59779",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:43.627468Z",
     "iopub.status.busy": "2022-07-31T02:35:43.627054Z",
     "iopub.status.idle": "2022-07-31T02:35:49.121223Z",
     "shell.execute_reply": "2022-07-31T02:35:49.120482Z"
    },
    "origin_pos": 7,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def read_voc_images(voc_dir, is_train=True):\n",
    "    \"\"\"读取所有VOC图像并标注\"\"\"\n",
    "    txt_fname = os.path.join(voc_dir, 'ImageSets', 'Segmentation',\n",
    "                             'train.txt' if is_train else 'val.txt')\n",
    "    mode = torchvision.io.image.ImageReadMode.RGB\n",
    "    with open(txt_fname, 'r') as f:\n",
    "        images = f.read().split()\n",
    "    features, labels = [], []\n",
    "    for i, fname in enumerate(images):\n",
    "        features.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'JPEGImages', f'{fname}.jpg')))\n",
    "        labels.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'SegmentationClass' ,f'{fname}.png'), mode))\n",
    "    return features, labels\n",
    "\n",
    "train_features, train_labels = read_voc_images(voc_dir, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f63278bd",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "绘制前5个输入图像及其标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9e7d1b4f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:49.124776Z",
     "iopub.status.busy": "2022-07-31T02:35:49.124389Z",
     "iopub.status.idle": "2022-07-31T02:35:49.763051Z",
     "shell.execute_reply": "2022-07-31T02:35:49.762382Z"
    },
    "origin_pos": 10,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 5\n",
    "imgs = train_features[0:n] + train_labels[0:n]\n",
    "imgs = [img.permute(1,2,0) for img in imgs]\n",
    "d2l.show_images(imgs, 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "391dcad4",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "列举RGB颜色值和类名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "112d1c1b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:49.766665Z",
     "iopub.status.busy": "2022-07-31T02:35:49.766271Z",
     "iopub.status.idle": "2022-07-31T02:35:49.772554Z",
     "shell.execute_reply": "2022-07-31T02:35:49.771945Z"
    },
    "origin_pos": 12,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "VOC_COLORMAP = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0],\n",
    "                [0, 0, 128], [128, 0, 128], [0, 128, 128], [128, 128, 128],\n",
    "                [64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0],\n",
    "                [64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128],\n",
    "                [0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0],\n",
    "                [0, 64, 128]]\n",
    "\n",
    "VOC_CLASSES = ['background', 'aeroplane', 'bicycle', 'bird', 'boat',\n",
    "               'bottle', 'bus', 'car', 'cat', 'chair', 'cow',\n",
    "               'diningtable', 'dog', 'horse', 'motorbike', 'person',\n",
    "               'potted plant', 'sheep', 'sofa', 'train', 'tv/monitor']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8bd0b81",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "查找标签中每个像素的类索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "05d474a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:49.775531Z",
     "iopub.status.busy": "2022-07-31T02:35:49.775180Z",
     "iopub.status.idle": "2022-07-31T02:35:49.780540Z",
     "shell.execute_reply": "2022-07-31T02:35:49.779935Z"
    },
    "origin_pos": 15,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def voc_colormap2label():\n",
    "    \"\"\"构建从RGB到VOC类别索引的映射\"\"\"\n",
    "    colormap2label = torch.zeros(256 ** 3, dtype=torch.long)\n",
    "    for i, colormap in enumerate(VOC_COLORMAP):\n",
    "        colormap2label[\n",
    "            (colormap[0] * 256 + colormap[1]) * 256 + colormap[2]] = i\n",
    "    return colormap2label\n",
    "\n",
    "def voc_label_indices(colormap, colormap2label):\n",
    "    \"\"\"将VOC标签中的RGB值映射到它们的类别索引\"\"\"\n",
    "    colormap = colormap.permute(1, 2, 0).numpy().astype('int32')\n",
    "    idx = ((colormap[:, :, 0] * 256 + colormap[:, :, 1]) * 256\n",
    "           + colormap[:, :, 2])\n",
    "    return colormap2label[idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c9a87b3",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "例如"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d5624cde",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:49.783668Z",
     "iopub.status.busy": "2022-07-31T02:35:49.783088Z",
     "iopub.status.idle": "2022-07-31T02:35:49.807532Z",
     "shell.execute_reply": "2022-07-31T02:35:49.806808Z"
    },
    "origin_pos": 17,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]]),\n",
       " 'aeroplane')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = voc_label_indices(train_labels[0], voc_colormap2label())\n",
    "y[105:115, 130:140], VOC_CLASSES[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70195c3c",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "使用图像增广中的随机裁剪，裁剪输入图像和标签的相同区域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d1cba440",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:49.817975Z",
     "iopub.status.busy": "2022-07-31T02:35:49.817371Z",
     "iopub.status.idle": "2022-07-31T02:35:50.264971Z",
     "shell.execute_reply": "2022-07-31T02:35:50.264111Z"
    },
    "origin_pos": 22,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def voc_rand_crop(feature, label, height, width):\n",
    "    \"\"\"随机裁剪特征和标签图像\"\"\"\n",
    "    rect = torchvision.transforms.RandomCrop.get_params(\n",
    "        feature, (height, width))\n",
    "    feature = torchvision.transforms.functional.crop(feature, *rect)\n",
    "    label = torchvision.transforms.functional.crop(label, *rect)\n",
    "    return feature, label\n",
    "\n",
    "imgs = []\n",
    "for _ in range(n):\n",
    "    imgs += voc_rand_crop(train_features[0], train_labels[0], 200, 300)\n",
    "\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs[::2] + imgs[1::2], 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14c8d5aa",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "自定义语义分割数据集类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f86ee7b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:50.269573Z",
     "iopub.status.busy": "2022-07-31T02:35:50.268903Z",
     "iopub.status.idle": "2022-07-31T02:35:50.277416Z",
     "shell.execute_reply": "2022-07-31T02:35:50.276651Z"
    },
    "origin_pos": 25,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "class VOCSegDataset(torch.utils.data.Dataset):\n",
    "    \"\"\"一个用于加载VOC数据集的自定义数据集\"\"\"\n",
    "\n",
    "    def __init__(self, is_train, crop_size, voc_dir):\n",
    "        self.transform = torchvision.transforms.Normalize(\n",
    "            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "        self.crop_size = crop_size\n",
    "        features, labels = read_voc_images(voc_dir, is_train=is_train)\n",
    "        self.features = [self.normalize_image(feature)\n",
    "                         for feature in self.filter(features)]\n",
    "        self.labels = self.filter(labels)\n",
    "        self.colormap2label = voc_colormap2label()\n",
    "        print('read ' + str(len(self.features)) + ' examples')\n",
    "\n",
    "    def normalize_image(self, img):\n",
    "        return self.transform(img.float() / 255)\n",
    "\n",
    "    def filter(self, imgs):\n",
    "        return [img for img in imgs if (\n",
    "            img.shape[1] >= self.crop_size[0] and\n",
    "            img.shape[2] >= self.crop_size[1])]\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        feature, label = voc_rand_crop(self.features[idx], self.labels[idx],\n",
    "                                       *self.crop_size)\n",
    "        return (feature, voc_label_indices(label, self.colormap2label))\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.features)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac2699a4",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e0271c09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:35:50.281399Z",
     "iopub.status.busy": "2022-07-31T02:35:50.280796Z",
     "iopub.status.idle": "2022-07-31T02:36:02.798551Z",
     "shell.execute_reply": "2022-07-31T02:36:02.797855Z"
    },
    "origin_pos": 27,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1114 examples\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1078 examples\n"
     ]
    }
   ],
   "source": [
    "crop_size = (320, 480)\n",
    "voc_train = VOCSegDataset(True, crop_size, voc_dir)\n",
    "voc_test = VOCSegDataset(False, crop_size, voc_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8e2dbd2c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:36:02.803147Z",
     "iopub.status.busy": "2022-07-31T02:36:02.802643Z",
     "iopub.status.idle": "2022-07-31T02:36:04.438105Z",
     "shell.execute_reply": "2022-07-31T02:36:04.437259Z"
    },
    "origin_pos": 30,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 3, 320, 480])\n",
      "torch.Size([64, 320, 480])\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "train_iter = torch.utils.data.DataLoader(voc_train, batch_size, shuffle=True,\n",
    "                                    drop_last=True,\n",
    "                                    num_workers=d2l.get_dataloader_workers())\n",
    "for X, Y in train_iter:\n",
    "    print(X.shape)\n",
    "    print(Y.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7df0f391",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "整合所有组件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "45e57eff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-31T02:36:04.442035Z",
     "iopub.status.busy": "2022-07-31T02:36:04.441778Z",
     "iopub.status.idle": "2022-07-31T02:36:04.448986Z",
     "shell.execute_reply": "2022-07-31T02:36:04.448299Z"
    },
    "origin_pos": 33,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def load_data_voc(batch_size, crop_size):\n",
    "    \"\"\"加载VOC语义分割数据集\"\"\"\n",
    "    voc_dir = d2l.download_extract('voc2012', os.path.join(\n",
    "        'VOCdevkit', 'VOC2012'))\n",
    "    num_workers = d2l.get_dataloader_workers()\n",
    "    train_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(True, crop_size, voc_dir), batch_size,\n",
    "        shuffle=True, drop_last=True, num_workers=num_workers)\n",
    "    test_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(False, crop_size, voc_dir), batch_size,\n",
    "        drop_last=True, num_workers=num_workers)\n",
    "    return train_iter, test_iter"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "language_info": {
   "name": "python"
  },
  "rise": {
   "autolaunch": true,
   "enable_chalkboard": true,
   "overlay": "<div class='my-top-right'><img height=80px src='http://d2l.ai/_static/logo-with-text.png'/></div><div class='my-top-left'></div>",
   "scroll": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}